ITS632 Golden Gate University San Francisco Data Mining Exam Questions
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1.True / False
Our use of association analysis will yield the same frequent itemsets and strong association rules whether a specific item occurs once or three times in an individual transaction.
ANSWER:
2.True / False
A density-based clustering algorithm can generate non-globular clusters.
ANSWER:
3.True / False
The k-means clustering algorithm will automatically find the best value of k as part of its normal operation.
ANSWER:
4. True / False
In association rule mining the generation of the frequent itemsets is the computational intensive step.
ANSWER:
5. In the following figure, there are two clusters. They are connected by a line which represents the distance used to determine inter-cluster similarity.
Which inter-cluster similarity metric does this line represent?
a. Min
b. Max
c. Group Average
d. Distance between centroids
ANSWER (JUST INDICATE THE LETTER OF YOUR RESPONSE DO NOT USE WORDS):
6. Are the two clusters shown below well separated?
a.Yes
b. No
ANSWER (JUST INDICATE THE LETTER OF YOUR RESPONSE DO NOT USE WORDS):
7. Explain your answer to item #6.
ANSWER:
8. Using a maximum of 20 words for each response, explain why how anomaly detection is vital in each of the following instances.
a.Intrusion Detection Systems
ANSWER (20 words or less):
b. Fraud Detection in Transactions
ANSWER (20 words or less):
c. Electronic Sensor Events
ANSWER (20 words or less):
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